Behnaz Arzani

• University of Pennsylvania

Many problems that cloud operators solve are computationally expensive, and operators often use heuristic algorithms (that are faster and scale better than optimal) to solve them more efficiently. Heuristic analyzers enable operators to find when and by how much their heuristics underperform. However, these tools do not provide enough detail for op...

Many problems that cloud operators solve are computationally expensive, and operators often use heuristic algorithms (that are faster and scale better than optimal) to solve them more efficiently. Heuristic analyzers enable operators to find when and by how much their heuristics underperform. However, these tools do not provide enough detail for op...

Large-scale deployments of low Earth orbit (LEO) satellites collect massive amount of Earth imageries and sensor data, which can empower machine learning (ML) to address global challenges such as real-time disaster navigation and mitigation. However, it is often infeasible to download all the high-resolution images and train these ML models on the...

Continuously monitoring a wide variety of performance and fault metrics has become a crucial part of operating large-scale datacenter networks. In this work, we ask whether we can reduce the costs to monitor -- in terms of collection, storage and analysis -- by judiciously controlling how much and which measurements we collect. By positing that we...

Automated machine learning (AutoML) systems aim to enable training machine learning (ML) models for non-ML experts. A shortcoming of these systems is that when they fail to produce a model with high accuracy, the user has no path to improve the model other than hiring a data scientist or learning ML -- this defeats the purpose of AutoML and limits...

Clouds gather a vast volume of telemetry from their networked systems which contain valuable information that can help solve many of the problems that continue to plague them. However, it is hard to extract useful information from such raw data. Machine Learning (ML) models are useful tools that enable operators to either leverage this data to solv...

In spite of much progress and many advances, cost-effective, high-quality video delivery over the internet remains elusive. To address this ongoing challenge, we propose Sunstar, a solution that leverages simultaneous downloads from multiple servers to preserve video quality. The novelty in Sunstar is not so much in its use of multiple servers but...

Cloud customers require highly reliable and performant leased datacenter infrastructure to deliver quality service for their users. It is thus critical for cloud providers to quickly detect and mitigate infrastructure faults. While much is known about managing faults that arise in the datacenter physical infrastructure (i.e., network and server equ...

Network failures continue to plague datacenter operators as their symptoms may not have direct correlation with where or why they occur. We introduce 007, a lightweight, always-on diagnosis application that can find problematic links and also pinpoint problems for each TCP connection. 007 is completely contained within the end host. During its two...

Today, root cause analysis of failures in data centers is mostly done through manual inspection. More often than not, cus- tomers blame the network as the culprit. However, other components of the system might have caused these failures. To troubleshoot, huge volumes of data are collected over the entire data center. Correlating such large volumes...

The performance of networks that use the Internet Protocol is sensitive to precise configuration of many low-level parameters on each network device. These settings govern the action of dynamic routing protocols, which direct the flow of traffic; in order to ensure that these dynamic protocols all converge to produce some 'optimal' flow, each param...

The paper seeks to broaden our understanding of MPTCP and focuses on the impact that initial sub-path selection can have on performance. Using empirical data, it demonstrates that which sub-path is chosen to start an MPTCP connection can have unintuitive consequences. Using numerical analysis and a model-driven investigation, the paper elucidates a...

With increasing deployment of Multipath TCP (MPTCP) in multihoming and data enter scenarios, there is a need to understand how its performance is affected in practice-both by traditional factors such as RTT measurements, and by new multipath-specific considerations such as sub flow selection. We carried out an initial but comprehensive study using...

Wireless mesh networks hold the promise of rapid and flexible deployments of communication facilities. This potential notwithstanding, the often erratic behavior of multihop wireless transmissions is limiting the range of applications that such networks can target. In this paper we investigate the feasibility and benefits of a routing protocol expl...

Wireless mesh networks hold the promise of rapid and flexible deployments of communication facilities. This potential notwithstanding, the often erratic behavior of multihop wireless transmissions is limiting the range of applications that such networks can target. In this paper we investigate the feasibility and benefits of a routing protocol expl...